I'm facing a new problem when trying to load old vectors in a geometry optimization. I simply resubmitted a job that hadn't converged by specifying the input vectors (which I have done many times without any problem), but this time, I get a new warning about a basis mismatch before nwchem fails to load the movecs file :

Either an incorrect movecs file was
specified, or linear dependence has changed,
or the basis name was changed.

Loading old vectors from job with title :

Load of old vectors failed. Forcing atomic density guess

The thing is, I haven't changed anything in the input file (same basis, same atoms, same everything). I tried resubmitting the job with another set of older vectors (again from the same geometry) and got the same error. It doesn't seem like the vector file is corrupted as I have already loaded this same file previously without any problem. In fact, it looks like it always fails at the same step of the geometry optimization even though there is nothing special about that step. Has anyone ever seen this?

What you are dealing with is a change in the number of linear dependent basis functions as a result of a reasonably large change in geometry during the optimization. One way to get around this is to set the number of linear dependent functions that can be discarded to set using "set lindep: n_dep 0" or to adjust the linear dependence tolerance using "set lindep:tol 1.0d-5" or some other value.

I've tried everything, restarted the calculation from a previous geometry and building a new guess for the vectors. It always ends up converging to the same vectors that fail on the next step. I can't get passed this point. I know I'm supposed to have 13 linear dependencies and that the calculation fails when there are 14, but setting n_dep to 1 doesn't change anything, nor does changing the tolerance. Whatever I do I always get 14 linear dependencies and this message about the the basis mismatch. I also tried to change the geometry a little manually so that the calculation doesn't follow the exact same optimization steps, but it didn't help. This is really bothering me. Is there any workaround?